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An aggregated clustering approach using multi-ant colonies algorithms

PATTERN RECOGNITION 2006年第7期39卷 1278-1289页

作者： Yang, Yan Kamel, Mohamed S. SW Jiaotong Univ Sch Informat Sci & Technol Chengdu 610031 Peoples R China Univ Waterloo Pattern Anal & Machine Intelligence Lab Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

This paper presents a multi-ant colonies approach for clustering data that consists of some parallel and independent ant colonies and a queen ant agent. Each ant colony process takes different types of ants moving speed and different versions of the probability conversion function to generate various clustering results with an ant-based clustering algorithm. These results are sent to the queen ant agent and combined by a hypergraph model to calculate a new similarity matrix. The new similarity matrix is returned back to each ant colony process to re-cluster the data using the new information. Experimental evaluation shows that the average performance of the aggregated multi-ant colonies algorithms outperforms that of the single ant-based clustering algorithm and the popular K-means algorithm. The result also shows that the lowest outliers strategy for selecting the current data set has the best performance quality. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： ant algorithm multi-ant colonies clustering aggregated clustering

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ant Colony Optimization algorithm for Fuzzy Transport Modelling

Ant Colony Optimization Algorithm for Fuzzy Transport Modell...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Stefka Fidanova Olympia Roeva Maria Ganzha IICT BAS Sofia Bulgaria IBPhBME BAS Sofia Bulgaria SRI PAS Warsaw Poland

ISBN: (数字)9788395541674

ISBN: (纸本)9781728141473

Public transport plays an important role in our live. It is very important to have a reliable service. Up to 1000 km, trains and buses play the main role in the public transport. The number of the people and which kind of transport they prefer is important information for transport operators. In this paper is proposed algorithm for transport modeling and passenger flow, based on ant Colony Optimization method. The problem is described as multi-objective optimization problem. There are two optimization purposes: minimal transportation time and minimal price. Some fuzzy element is included. When the price is in a predefined interval it is considered the same. Similar for the starting traveling time. The aim is to show how many passengers will prefer train and how many will prefer buses according their preferences, the price or the time.

关键词： Motor buses transport Public Transit ant colony optimization passenger flow ant algorithm TRAIN Prices algorithms Minimal Fuzzy Modeling

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An optimization method inspired by "chaotic" ant behavior

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INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 2006年第8期16卷 2351-2364页

作者： Li, Lixiang Yang, Yixian Peng, Haipeng Wang, Xiangdong Beijing Univ Posts & Telecommun Dept Informat Engn Beijing 100876 Peoples R China Xidian Univ State Key Lab Integrated Serv Network Xian 710071 Peoples R China Shenyang Univ Technol Sch Informat Sci & Engn Shenyang 110023 Peoples R China

Inspired by the behavior of the ants in nature, we propose an optimization method, which combines the chaotic behavior of individual ants with the intelligent optimization action of an ant colony. Our method includes both effects of chaotic dynamics and swarm-based search. It is a deterministic process different from the conventional ant algorithm. The nonlinear dynamics of the proposed method are analyzed, and we show how the algorithm, called chaotic ant swarm optimization, can be applied to numerical optimization problems with encouraging results.

关键词： chaotic search numerical optimization biologically inspired algorithm particle swarm ant algorithm chaotic ant swarm

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Voltage and Power Regulation for a Sample Power System using ant Colony System Based PID controller

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JOURNAL OF ELECTRICAL SYSTEMS 2012年第4期8卷 397-410页

作者： Besheer, A. H. Bensenouci, A. King Abdulaziz Univ Fac Engn Elect & Comp Engn Dept POB 80204 Jeddah 21589 Saudi Arabia Univ Tabuk Fac Engn Elect Engn Dpt Tabuk Saudi Arabia Minoufiya Univ Al Minufya Egypt

This paper introduces a social inspired optimization based control method for driving a sample power system in terms of its output power and terminal voltage to achieve prescribed desired values. In particular, a well known Proportional Integral Derivative (PID) controller is fine tuned using ant colony system algorithm and tested on a simulated AC turbo generator power system that comprises a synchronous generator connected to a large network (infinite bus bar) via a step-up transformer and a transmission line. To show the effectiveness of the proposed ant colony based PID controller, the system nonlinearities are introduced. Satisfactory dynamic and steady state performance of the simulated linearized and non-linearized models for the proposed sample power system reflects the appealing of the suggested control technique over the traditional control methods.

关键词： Power system control turbo-generator optimal PID design ant algorithm

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Simultaneous management of water and wastewater using ant and artificial neural network (ANN) algorithms

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INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2019年第10期16卷 5835-5856页

作者： Rastegaripour, F. Saboni, M. S. Shojaei, S. Tavassoli, A. Univ Torbat Heidarieh Dept Agr Econ Torbat Heidarieh Iran Univ Mashhad Dept Agr Econ Mashhad Razavi Khorasan Iran Islamic Azad Univ Zahedan Branch Young Researchers & Elite Club Zahedan Iran Payame Noor Univ Dept Agr Zahedan Iran

In the present study, simultaneous management of water and wastewater was examined using ant and artificial neural network algorithms. ant algorithm is one of the most meta-heuristic algorithms to solve optimization problems. The data were collected in a monthly time series from the Regional Water Organization of Khorasan Razavi during 1998-2016. Water flow data were initially estimated in the study. In this regard, different structures of the back propagation network (1, 2, 3, 4 and 5 nodes in the hidden layer) were designed by using logistic activation function in order to evaluate the efficiency of ANN model and its comparison with the ARIMA method in predicting the time series of the flows for the time horizons of next 3, 6, 9 and 12 month. The output data of each network were finally compared with actual data to evaluate the efficiency of the model and its comparison with ARIMA model using the evaluation criteria of models. Water resources were, then, allocated to drinking, agricultural and industrial sectors using the ant algorithm. According to the results of the total consumption of drinking water for the industrial sector, the southeast and northwest of Mashhad have the greatest amount of water. In other words, the northeastern and southwestern parts of Mashhad have the least amount of water for the industrial sector. And so, there must be a higher priority to water scarcity in these two regions than the other areas.

关键词： ant algorithm Artificial neural network Water Wastewater Mashhad plain

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Multi-robot exploration of unknown environments with identification of exploration completion and post-exploration rendez-vous using ant algorithms

Multi-robot exploration of unknown environments with identif...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Mihai Andries Francois Charpillet Inria Villers-les-Nancy F-54600 France

ISBN: (纸本)9781467363563

This paper presents a new ant algorithm for the navigation of several robots, whose objective is to autonomously explore an unknown environment. When the coverage is completed, all robots move to a previously defined meeting point. The approach that we propose in this paper for solving this problem, considers that the robots build, while moving, a common and shared representation of the environment. In this representation, the environment is viewed as a graph (typically a set of connected cells in a regular grid), each grid cell having a local memory able to store a limited amount of data. A robot can write numbers on the cell on which it is lying. It can also read the values of the cells in its neighborhood, and perform some simple operations, such as computing the minimum of a set of values. Each robot is capable, contrary to most ant-based approaches, to determine, in a distributed way, when the environment coverage has completed. Few ant algorithms can do that. Brick & Mortar is one of them and this is why it retains a central place in our proposition. The novelty of our approach is that, due to an emerging property of the underlying algorithm, agents will finish their exploration at a pre-defined evacuation point. In addition, several improvements of the original Brick&Mortar algorithm are proposed in this paper, such as the possibility to use better local strategies at the robot level (using, for example, LRTA*). The paper also presents a set of benchmarks against the best existing ant algorithms on several widespread graph topologies.

关键词： Robot Unknown environments ant algorithm Exploration ants algorithms Environments Coverage

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ant-based IP traceback

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EXPERT SYSTEMS WITH APPLICATIONS 2008年第4期34卷 3071-3080页

作者： Lai, Gu Hsin Chen, Chia-Mei Jeng, Bing-Chiang Chao, Willanis Natl Sun Yat Sen Univ Dept Informat Management Kaohsiung 804 Taiwan

The denial-of-service (DoS) attacks with the source IP address spoofing techniques has become a major threat to the Internet. An intrusion detection system is often used to detect DoS attacks and to coordinate with the firewall to block them. However, DoS attack packets consume and may exhaust all the resources, causing degrading network performance or, even worse, network breakdown. A proactive approach to DoS attacks is allocating the original attack host(s) issuing the attacks and stopping the malicious traffic, instead of wasting resources on the attack traffic. In this paper, an ant-based traceback approach is proposed to identify the DoS attack origin. Instead of creating a new type or function or processing a high volume of fine-grained data used by previous research, the proposed traceback approach uses flow level information to identify the origin of a DoS attack. Two characteristics of ant algorithm, quick convergence and heuristic, are adopted in the proposed approach on finding the DoS attack Path. Quick convergence efficiently finds out the origin of a DoS attack;heuristic gives the solution even though partial flow information is provided by the network. The proposed method is evaluated through simulation on various network environments and two simulated real networks, NSFNET and DFN. The simulation results show that the proposed method can successfully and efficiently find the DoS attack path in various simulated network environments, with full and partial flow information provided by the networks. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： IP traceback NetFlow DoS ant algorithm

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LAAT: Locally Aligned ant Technique for Discovering Multiple Faint Low Dimensional Structures of Varying Density

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2023年第6期35卷 6014-6027页

作者： Taghribi, Abolfazl Bunte, Kerstin Smith, Rory Shin, Jihye Mastropietro, Michele Peletier, Reynier F. Tino, Peter Univ Groningen Fac Sci & Engn NL-9700 AV Groningen Netherlands Univ Tecn Federico Santa Maria Dept Fis San Joaquin 3939 Chile Korea Astron & Space Sci Inst Daejeon 34055 South Korea Univ Ghent B-9000 Ghent Belgium Univ Groningen Kapteyn Inst NL-9700 AV Groningen Netherlands Univ Birmingham Sch Comp Sci Birmingham B15 2TT England

Dimensionality reduction and clustering are often used as preliminary steps for many complex machine learning tasks. The presence of noise and outliers can deteriorate the performance of such preprocessing and therefore impair the subsequent analysis tremendously. In manifold learning, several studies indicate solutions for removing background noise or noise close to the structure when the density is substantially higher than that exhibited by the noise. However, in many applications, including astronomical datasets, the density varies alongside manifolds that are buried in a noisy background. We propose a novel method to extract manifolds in the presence of noise based on the idea of ant colony optimization. In contrast to the existing random walk solutions, our technique captures points that are locally aligned with major directions of the manifold. Moreover, we empirically show that the biologically inspired formulation of ant pheromone reinforces this behavior enabling it to recover multiple manifolds embedded in extremely noisy data clouds. The algorithm performance in comparison to state-of-the-art approaches for noise reduction in manifold detection and clustering is demonstrated, on several synthetic and real datasets, including an N-body simulation of a cosmological volume.

关键词： Manifolds Noise reduction Manifold learning Point cloud compression Noise measurement Eigenvalues and eigenfunctions Clustering algorithms ant algorithm Markov chain multiple manifold detection evolutionary computation

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Application of a max-min ant system to joint layout and size optimization of pipe networks

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ENGINEERING OPTIMIZATION 2006年第3期38卷 299-317页

作者： Afshar, M. H. Iran Univ Sci & Technol Dept Civil Engn Tehran 16844 Iran

The application of a max-min ant algorithm to the layout and size optimization of pipe networks is described in this paper. The formulation conventionally used for the pipe size optimization of networks with fixed layout is extended to account for the layout determination of the networks. This is achieved by including new constraints regarding the reliability of the network and modifying some of the constraints of the optimization problem. A deterministic concept of reliability is used in which the number of independent paths from source nodes to each of the demand nodes is considered as a measure of reliability. The method starts with a predefined layout which includes all possible links. The method is capable of designing the layout and pipe sizes of water distribution networks of predefined reliability including tree-like and looped networks. It is also shown that a layout optimization of a network followed by size optimization does not lead to an optimal or a near-optimal solution. This emphasizes the need for simultaneous layout and size optimization of networks if an optimal or near-optimal solution is desired. The performance of the method for layout and pipe size optimization of pipe networks is tested against two benchmark examples in the literature and the results are presented. The first example is considered to show the necessity of joint layout and size optimization even for the simple tree networks while the second example is considered to illustrate the efficiency of the proposed method for layout and size optimization of real-world networks with different levels of reliability.

关键词： pipe networks ant algorithm tree and looped networks layout and pipe size optimization

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FPGA implementation of population-based ant colony optimization

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APPLIED SOFT COMPUTING 2004年第3期4卷 303-322页

作者： Scheuermann, B So, K Guntsch, M Middendorf, M Diessel, O ElGindy, H Schmeck, H Univ Karlsruhe TH Inst AIFB Karlsruhe Germany Univ New S Wales Kensington NSW 2033 Australia Univ Leipzig Inst Comp Sci Leipzig Germany

We present a hardware implementation of population-based ant colony optimization (P-ACO) on field-programmable gate arrays (FPGAs). The ant colony optimization meta-heuristic is adopted from the natural foraging behavior of real ants and has been used to find good solutions to a wide spectrum of combinatorial optimization problems. We describe the P-ACO algorithm and present a circuit architecture that facilitates efficient FPGA implementations. The proposed design shows modest space requirements but leads to a significant reduction in runtime over software-based solutions. Several modifications and extensions of the basic algorithm are also presented, including the approximation of the heuristic function by a small, dynamically changing set of favorable decisions. (C) 2004 Elsevier B.V. All rights reserved.

关键词： ant colony optimization ant algorithm field-programmable gate array FPGA

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